Pulse MCP Server
An MCP server that exposes Moody's Pulse (Cortera) trade-credit data with grounded knowledge-base context, enabling search, report retrieval, and explanation of metrics and use cases.
README
Pulse MCP Server
An MCP server that exposes Moody's Pulse (Cortera) trade-credit data with grounded knowledge-base context. Every report section and metric is linked to a local knowledge base (pulse-kb/) so the server can explain what each value means, how it's computed, how it ties into the wider Moody's data estate, and which use cases it serves.
Tools
| Tool | Purpose |
|---|---|
search_business |
Find a company → linkId |
get_report |
Full Deep Dive Report (entire JSON) |
get_report_section |
Pull specific sections by canonical name or natural-language alias |
list_report_sections |
List all sections with their plain-English meaning |
explain_section |
Explain a section (definition + KB source + cross-data-estate ties) |
explain_metric |
Explain a metric / field (CPR, DR, DBT, etc.) |
list_metrics |
Catalog of metrics in the registry |
get_use_case_briefing |
Surface Pulse signals + framework for a use case (surety, trade_credit, dno, portfolio, tprm, submission_triage, industry_macro) |
read_kb |
Read a KB doc by relative path for deep dives |
Prerequisites
- Python 3.10+
- Pulse (Cortera) API credentials
Install
pip install -r requirements.txt
Configure
Copy the example env file and fill in your credentials:
cp .env.example .env
Then edit .env:
PULSE_USER=your-pulse-username
PULSE_PASSWORD=your-pulse-password
Register with an MCP client
Add to your MCP client config (e.g. .mcp.json or claude_desktop_config.json):
{
"mcpServers": {
"pulse": {
"command": "python",
"args": ["C:/path/to/pulse-mcp/server.py"]
}
}
}
Project layout
pulse-mcp/
├── server.py # FastMCP server + tool definitions
├── kb_registry.py # section aliases, metrics, use-case frameworks
├── pulse-kb/ # knowledge-base docs (definitions, cross-estate ties)
├── requirements.txt
├── .env.example # template — copy to .env (gitignored)
└── Dockerfile
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.